Healthcare Chatbots: Benefits, Future, Use Cases, Development

In a recent study, licensed healthcare professionals were tasked with evaluating and comparing responses from doctors and ChatGPT to health-related inquiries on social media. ChatGPT responses outperformed doctors’ responses in terms of both quality and empathy, earning significantly higher ratings in 79 percent of the 585 evaluations. Medical chatbots respond to prompts and data shared by users about their health to offer relevant information, guidance, and advice. As healthcare systems grapple with staffing shortages and overburdened resources, medical chatbots could offer a digital lifeline. To facilitate this assessment, we develop and present an evaluative framework that classifies the key characteristics of healthbots.

Many institutions have AI that gets essential data and notifies healthcare experts when required. Chatbots’ reminder messages can make it far less possible that patients will forget to attend. Chatbot developers must use different chatbots for involving and offering value to their audience. You need to know your audience and what suits them most and which chatbot works for what setting. Every chatbot you create that targets to offer healthcare suggestions must intensely ponder the rules that regulate it. Medical providers are already utilizing different kinds of AI, such as machine learning or predictive analysis for identifying different problems.

What is chatbot in healthcare?

Chatbots may not know every appropriate factor related to the patient or could make a wrong diagnosis, and the financial significance of an error can be massive. You can foun additiona information about ai customer service and artificial intelligence and NLP. But chatbots alone can deal with one interaction or 1000 interactions with no problem. Now several providers change this segment into an interactive chatbot feature on their homepage dedicated to answering basic queries.

Using chatbots for healthcare helps patients to contact the doctor for major issues. A healthcare chatbot can serve as an all-in-one solution for answering all of a patient’s general questions in a matter of seconds. It can ask users a series of questions about their symptoms and provide preliminary assessments or suggestions based on the information provided. It is suitable to deliver general healthcare knowledge, including information about medical conditions, medications, treatment options, and preventive measures. Besides, it can collect and analyze data from wearable devices or other sources to monitor users’ health parameters, such as heart rate or blood pressure, and provide relevant feedback or alerts. ChatGPT is capable of generating human-like responses to a wide range of queries, making it an ideal tool for healthcare applications.

It’s recommended to develop an AI chatbot as a distinctive microservice so that it can be easily connected with other software solutions via API. It’s advisable to involve a business analyst to define the most required use cases. Also, they will help you define the flow of every use case, including input artifacts and required third-party software integrations. With each answer you give the chatbot, it eliminates a couple of diagnosis options until it finally lands on the most likely ones. Afterward, the chatbot helps you decide on the next steps and choose the best follow-up variant that suits you the best, both in terms of money and convenience.

There’s no doubt that their power will continue to rise, revolutionizing the way people interact with businesses and enhancing customer experiences. These mental health chatbots increase access to support and show promising results comparable to human-led treatment based on early studies. According to research by Accenture, scaling healthcare chatbots could result in over $3 billion in annual cost savings for the US healthcare system alone by 2023. Another study found that 70% of healthcare organizations are currently piloting or planning to pilot chatbots. While being seriously impacted by the COVID-19, the healthcare industry is steadily gaining traction in terms of its digital transformation and is adopting more and more innovative technologies on a regular basis. Chatbots, being among the most affordable solutions, have become valuable assets for healthcare organizations worldwide, and their value is recognized by both medical professionals and patients.

In this comprehensive guide, we‘ll explore six high-impact chatbot applications in healthcare, real-world examples, implementation best practices, evaluations of leading solutions, and predictions for the future. Read on to gain valuable insights you can apply to your healthcare chatbot initiatives. It can be done via different ways, by asking questions or through a questionnaire that a patient fills in themselves. In this way, a patient learns about their condition and its severity and the bot, in return, suggests a treatment plan or even notifies the doctor in case of an emergency. There are several reasons why chatbots help healthcare organizations elevate their patient care – let’s look at each in a bit of detail.

Chatbots: The Future of Healthcare

With the rapidly increasing applications of chatbots in health care, this section will explore several areas of development and innovation in cancer care. Various examples of current chatbots provided below will illustrate their ability to tackle the triple aim of health care. The specific use case of chatbots in oncology with examples of actual products and proposed designs are outlined in Table 1.

One of the most fascinating applications of AI and automation in healthcare is using chatbots. Chatbots in healthcare are computer programs designed to simulate conversation with human users, providing personalized assistance and support. Over time, chatbot algorithms became capable of more complex rules-based programming and even natural language processing, enabling customer queries to be expressed in a conversational way. This gave rise to a new type of chatbot, contextually aware and armed with machine learning to continuously optimize its ability to correctly process and predict queries through exposure to more and more human language. There are countless opportunities to automate processes and provide real value in healthcare.

The next classification is based on goals with the aim of achievement, subdivided into informative, conversational, and task based. Response generation chatbots, further classified as rule based, retrieval based, and generative, account for the process of analyzing inputs and generating responses [16]. Finally, human-aided classification incorporates human computation, which provides more flexibility and robustness but lacks the speed to accommodate more requests [17]. To get the most from an organization’s existing data, enterprise-grade chatbots can be integrated with critical systems and orchestrate workflows inside and outside of a CRM system. Chatbots can handle real-time actions as routine as a password change, all the way through a complex multi-step workflow spanning multiple applications.

This not only saves time but also reduces unnecessary visits to healthcare facilities. To illustrate further how beneficial chatbots can be in streamlining appointment scheduling in health systems, let’s consider a case study. In a busy medical practice, Dr. Smith’s team was overwhelmed with numerous phone calls and manual paperwork related to appointments in their health system. One of the key advantages of using chatbots for scheduling appointments is their ability to integrate with existing systems. These intelligent bots can instantly check doctors’ availability in real-time before confirming appointments. This integration ensures that patients are promptly assigned to an available doctor without any delays or confusion.

Conversational UI: Best Practices & Case Studies in 2024

But even if the conversational bot does not have an innovative technology in its backpack, it can still be a highly valuable tool for quickly offering the needed information to a user. The healthcare industry is constantly embracing technological advancements, as every new innovation brings significant improvements to patient care and to work processes of medical professionals. And while some innovations may be too complex or expensive to implement, there is one that is highly affordable and efficient, and it’s a healthcare chatbot. For instance, chatbots can engage patients in their treatment plans, provide educational content, and encourage lifestyle changes, leading to better health outcomes. This interactive model fosters a deeper connection between patients and healthcare services, making patients feel more involved and valued.

The chatbot is available in Finnish, Swedish and English, and it currently administers 17 separate symptom assessments. First, it can perform an assessment of a health problem or symptoms and, second, more general assessments of health and well-being. Third, it can perform an ‘assessment of a sickness or its risks’ and guide ‘the resident to receive treatment in services promoting health and well-being within Omaolo and in social and health services external to’ it (THL 2020, p. 14). Fourth, it offers quality-of-life surveys, oral health surveys and health coaching.

Based on your information, the bot suggests self-care measures you can take at home. If your symptoms seem serious, the chatbot will advise you to seek medical attention. Chatbots are frequently used to assist in customer service to handle common inquiries, answer FAQs, and provide 24/7 support. They can resolve issues quickly and end up routing complex problems to human agents when necessary. One of the best examples of such chatbots is Ada, which was created by scientists, engineers, and doctors. Enriched with NLP and AI capabilities, Ada can help patients determine potential ailments and suggest possible treatments easily.

The platform automates care along the way by helping to identify high-risk patients and placing them in touch with a healthcare provider via phone call, telehealth, e-visit, or in-person appointment. Chatbots may even collect and process co-payments to further streamline the process. Many healthcare service providers are transforming FAQs by incorporating an interactive healthcare chatbot to respond to users’ general questions.

If you look up articles about flu symptoms on WebMD, for instance, a chatbot may pop up with information about flu treatment and current outbreaks in your area. When you are ready to invest in conversational AI, you can identify the top vendors using our data-rich vendor list on voice AI or chatbot platforms. Chatbots collect patient information, name, birthday, contact information, current doctor, last visit to the clinic, and prescription information. The chatbot submits a request to the patient’s doctor for a final decision and contacts the patient when a refill is available and due. By using SalesIQ specifically, patients can initiate conversation in an all-in-one live chatbot platform.

This not only reduces operational expenses but also increases overall efficiency within healthcare facilities. One of the key benefits of using AI chatbots in healthcare is their ability to provide educational content. Patients can use chatbots to receive valuable information about their health conditions directly, empowering them with knowledge to make informed decisions about their well-being. Whether it’s explaining symptoms, treatment options, or medication instructions, chatbots serve as virtual assistants that ensure patients are well-informed about their medical concerns.

The cognitive behavioral therapy–based chatbot SMAG, supporting users over the Facebook social network, resulted in a 10% higher cessation rate compared with control groups [50]. Motivational interview–based chatbots have been proposed with promising results, where a significant number of patients showed an increase in their confidence and readiness to quit smoking after 1 week [92]. No studies have been found to assess the effectiveness of chatbots for smoking cessation in terms of ethnic, racial, geographic, or socioeconomic status differences.

• With chatbots implemented in cancer care, consultations for minor health concerns may be avoided, which allows clinicians to spend more time with patients who need their attention the most.
• As we navigate the evolving landscape of healthcare, the integration of AI-driven chatbots marks a significant leap forward.
• Conversational chatbots are built to be contextual tools that respond based on the user’s intent.

Chatbots’ role is always acceptable to be in improving the job of healthcare experts, instead of replacing them. They can eliminate costs dramatically and boost efficiency, reduce the pressure on healthcare professionals, and enhance patient results. For instance, chatbots will help users check their symptoms and depending on the diagnosis, schedule an appointment, answer to the queries, and provide direct telemedicine consultation with a doctor through video calls. The doctor will prescribe medicines after this consultation and the system will store the prescription. While using such software products, users might be afraid of sharing their data with bots.

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Promising progress has also been made in using AI for radiotherapy to reduce the workload of radiation staff or identify at-risk patients by collecting outcomes before and after treatment [70]. An ideal chatbot for health care professionals’ use would be able to accurately detect diseases and provide the proper course of recommendations, which are functions currently limited by time and budgetary constraints. Continual algorithm training and updates would be necessary because of the constant improvements in current standards of care.

As we balance the allure of AI and the need to protect people’s health, medical chatbots have the potential to improve access to health information—especially when it comes to health issues people typically don’t like to discuss. Chatbots can encourage people to seek help sooner and talk openly about their health. This article discusses medical chatbots, underlining their potential to reshape the healthcare landscape. We address prevalent concerns and highlight recent research findings indicating that chatbots may encourage individuals with sensitive health issues to seek help sooner.

It has been proven to be 95% accurate in differentiating between normal and cancerous images. A study of 3 mobile app–based chatbot symptom checkers, Babylon (Babylon Health, Inc), Your.md (Healthily, Inc), and Ada (Ada, Inc), indicated that sensitivity remained low at 33% for the detection of head and neck cancer [28]. The number of studies assessing the development, implementation, and effectiveness are still relatively limited compared with the diversity of chatbots currently available. Further studies are required to establish the efficacy across various conditions and populations.

But staffing customer service departments to meet unpredictable demand, day or night, is a costly and difficult endeavor. Even the simplest chatbots are manifesting human-like characteristics by the very fact of engaging in a conversation with you. On the other hand, if by AI we understand machine learning and decision-making processes, only some chatbots are “real” AI chatbots. Experts who understand the difference between a search engine’s capabilities and the tasks at which generative AI models excel predict the latter will not replace the former.

And there are many more chatbots in medicine developed today to transform patient care. Use case for chatbots in oncology, with examples of current specific applications or proposed designs. AI chatbots are nothing like the all-knowing and manipulative supervillains we see in movies, according to the companies behind them, at least. However, after seeing Microsoft’s Copilot chatbot, formerly Bing Chat, literally call itself the Joker and suggest users kill themselves, I’m having some serious doubts about that. Explore chatbot design for streamlined and efficient experiences within messaging apps while overcoming design challenges. Selecting the right chatbot platform can have a significant payoff for both businesses and users.

Healthcare professionals can’t reach and screen everyone who may have symptoms of the infection; therefore, leveraging AI health bots could make the screening process fast and efficient. With the growing spread of the disease, there comes a surge of misinformation and diverse conspiracy theories, which could potentially cause the pandemic curve to keep rising. Therefore, it has become necessary to leverage digital tools that disseminate authoritative healthcare information to people across the globe.

The search was further limited using the Interactive Advertising Bureau (IAB) categories “Medical Health” and “Healthy Living”. The IAB develops industry standards to support categorization in the digital advertising industry; 42Matters labeled apps using these standards40. Relevant apps on the iOS Apple store were identified; then, the Google Play store was searched use of chatbots in healthcare with the exclusion of any apps that were also available on iOS, to eliminate duplicates. Chatbot becomes a vital point of communication and information gathering at unforeseeable times like a pandemic as it limits human interaction while still retaining patient engagement. Hence, it’s very likely to persist and prosper in the future of the healthcare industry.

Data that is enabled for being distributed through bots can be sent as required, any time. Moreover, the transaction can be smoothly handed over to a human whenever required. This is how a chatbot functions like the one-stop-shop for responding to all basic inquiries in seconds. Patients don’t require calling the clinic or spending time on the site navigation for finding the data they require.

Now that you have understood the basic principles of conversational flow, it is time to outline a dialogue flow for your chatbot. This forms the framework on which a chatbot interacts with a user, and a framework built on these principles creates a successful chatbot experience whether you’re after chatbots for medical providers or patients. Machine learning applications are beginning to transform patient care as we know it.